Researchers from Brown and MIT suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequential sampling techniques.
The lab of George Karniadakis, professor of applied mathematics and engineering, leads the charge of developing physics-informed neural networks to diagnose and predict the severity of arterial aneurysms.